Skip to main content
Article
Enhancing Arabic Content Generation with Prompt Augmentation Using Integrated GPT and Text-to-Image Models
IMX 2023 - Proceedings of the 2023 ACM International Conference on Interactive Media Experiences
  • Wala Elsharif, Hamad Bin Khalifa University
  • James She, Hamad Bin Khalifa University
  • Preslav Nakov, Mohamed Bin Zayed University of Artificial Intelligence
  • Simon Wong, Hong Kong University of Science and Technology
Document Type
Conference Proceeding
Abstract

With the current and continuous advancements in the field of text-to-image modeling, it has become critical to design prompts that make the best of these model capabilities and guides them to generate the most desirable images, and thus the field of prompt engineering has emerged. Here, we study a method to use prompt engineering to enhance text-to-image model representation of the Arabic culture. This work proposes a simple, novel approach for prompt engineering that uses the domain knowledge of a state-of-the-art language model, GPT, to perform the task of prompt augmentation, where a simple, initial prompt is used to generate multiple, more detailed prompts related to the Arabic culture from multiple categories through a GPT model through a process known as in-context learning. The augmented prompts are then used to generate images enhanced for the Arabic culture. We perform multiple experiments with a number of participants to evaluate the performance of the proposed method, which shows promising results, specially for generating prompts that are more inclusive of the different Arabic countries and with a wider variety in terms of image subjects, where we find that our proposed method generates image with more variety 85 % of the time and are more inclusive of the Arabic countries more than 72.66 % of the time, compared to the direct approach.

DOI
10.1145/3573381.3596466
Publication Date
6-12-2023
Keywords
  • Arabic culture,
  • GPT,
  • Integrated systems,
  • Prompt engineering
Comments

IR conditions: non-described

Citation Information
Wala Elsharif, James She, Preslav Nakov and Simon Wong. "Enhancing Arabic Content Generation with Prompt Augmentation Using Integrated GPT and Text-to-Image Models" IMX 2023 - Proceedings of the 2023 ACM International Conference on Interactive Media Experiences (2023) p. 276 - 288 ISSN: 979-840070028-6
Available at: http://works.bepress.com/preslav-nakov/26/